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All Journal REINWARDTIA BERITA BIOLOGI Journal of Technology Informatics and Engineering
James Hunter, James
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Education

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Floristic Study of West Sumbawa, Indonesia Wiriadinata, Harry; Girmansyah, Deden; Hunter, James; Hoover, W. Scoot; Kartawinata, Kuswata
REINWARDTIA Vol 13, No 5 (2013): Vol. 13, No. 5
Publisher : Research Center for Biology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (452.088 KB) | DOI: 10.14203/reinwardtia.v13i5.423

Abstract

A floristic survey was undertaken in mountains forest of West Sumbawa and some surrounding lower forests, an area of Indonesia receiving limited biological study. Three hundred sixteen species of Angiosperms and ferns were collected from this area in 2004 and 2005. The collection represents 101 families and 234 genera.
KEKAYAAN BEGONIA TAMAN NASIONAL GUNUNG HALIMUN Wiriadinata, Harry; Girmansyah, Deden; Hoover, Scott; Hunter, James
BERITA BIOLOGI Vol 6, No 1 (2002)
Publisher : Research Center for Biology-Indonesian Institute of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (326.248 KB) | DOI: 10.14203/beritabiologi.v6i1.1174

Abstract

Begonias arc unique due to asymmetric leaves, and they have large variation on their coloration and hairiness. The flower is unisexual, male and female flowers are in separate branches.The fruit with or without wings of different size and shape.Those unique characters attract them as ornamental plants, Mts. Halimun National Park has many species of wild Begonias which can be found on the forest floor.They grow in group and have essential role in mountainous forest ecosystem. Exploration for wild Begonia within forest around Cikaniki,Cirnarasa. Koridor Cianten, Gn, Botol, Gn. Bintang Gading, Gn. Sanggabuana will be presented in this paper.
Off-Policy Evaluation and Conservative Policy Selection for Slot-Level Dynamic Bidding and Ranking on the Open Bandit Dataset (Small) Ye, Tong; Mu, Jinyi; Hunter, James
Journal of Technology Informatics and Engineering Vol. 5 No. 1 (2026): APRIL | JTIE : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v5i1.503

Abstract

Dynamic bidding and ranking systems must improve revenue or engagement while avoiding harmful regressions during deployment. This paper presents an end-to-end offline OPE and conservative policy-selection workflow for slot-level contextual bandit approximations of ranking decisions. Using the small Open Bandit Dataset (OBD-small) from ZOZOTOWN (ZOZO, Inc.), each logged row is treated as a context-dependent choice among discrete actions (items), with binary click rewards and logged propensity. This formulation is suitable at the slot level but does not capture full listwise ranking or multi-step offline reinforcement learning. Dynamic bidding and ranking systems must improve revenue or engagement while avoiding harmful regressions during deployment. This paper presents an end-to-end offline OPE and conservative policy-selection workflow for slot-level contextual bandit approximations of ranking decisions. Using the small Open Bandit Dataset (OBD-small) from ZOZOTOWN (ZOZO, Inc.), each logged row is treated as a context-dependent choice among discrete actions (items), with binary click rewards and logged propensity. This formulation is suitable at the slot level but does not capture full listwise ranking or multi-step offline reinforcement learning. Empirically, highly deterministic evaluation policies exhibit extreme variance under sparse clicks, while the logistic reward model remains weak (ROC-AUC ≈ 0.5), limiting DM/DR interpretability. Clipped-DR mixing yields only limited certified improvements: in the women’s campaign, gains appear only at moderate confidence (δ=0.10) and for caps up to M=5, whereas stricter or looser settings revert to baseline; in the men’s campaign, certification is largely absent. These findings demonstrate that OPE diagnostics and conservative mixing enable reproducible offline selection under uncertainty, but do not indicate deployment-ready improvements.
Co-Authors Deden Girmansyah, Deden Harry Wiriadinata, Harry Hoover, Scott Kuswata Kartawinata Mu, Jinyi W. Scoot Hoover, W. Scoot Ye, Tong